Rapid prediction of in-hospital mortality among adults with COVID-19 disease.
Rapid prediction of in-hospital mortality among adults with COVID-19 disease.
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DOI：
10.1371/journal.pone.0269813
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
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作者：
我们开发了一种简单的工具，仅在初次入院时即可获得评估结果，即可估计死于急性COVID-19疾病的概率。这项回顾性研究包括13，190名种族和民族多样化的成年人，他们在2020年3月1日至6月30日期间因COVID-19疾病而入住纽约市健康+医院（NYC H+H）系统。从电子病历中收集人口统计学特征、简单生命体征和常规临床实验室检查。建立了住院期间死亡风险的临床预测模型。平均年龄（四分位距）为58（45-72）岁; 5421（41%）例为女性，5258例为拉丁裔（40%），3805例为黑人（29%），1168例为白色（9%），2959例为其他（22%）。住院期间，2，875人（22%）死亡。使用单独的测试和验证样本，机器学习（梯度提升决策树）确定了八个变量-血氧饱和度，呼吸频率，收缩压和舒张压，脉率，血尿素氮水平，年龄和肌酐-预测死亡率，ROC曲线下面积（AUC）为94%。基于这些变量的评分将5，677人（46%）分类为低风险（评分为0），死亡风险为0.8%（95%置信区间，0.5-1.0%），674人（5.4%）为高风险（评分≥ 12分），死亡风险为97.6%（96.5-98.8%）;其余为中等风险。风险计算器可在https://danielevanslab.shinyapps.io/Covid_mortality/上获得。在患有COVID-19疾病的住院患者的多样化人群中，使用一些容易获得的反映疾病严重程度的生命体征的临床预测模型可以精确预测不同人群的住院死亡率，并可以快速帮助决定优先入院和重症监护。
We developed a simple tool to estimate the probability of dying from acute COVID-19 illness only with readily available assessments at initial admission. This retrospective study included 13,190 racially and ethnically diverse adults admitted to one of the New York City Health + Hospitals (NYC H+H) system for COVID-19 illness between March 1 and June 30, 2020. Demographic characteristics, simple vital signs and routine clinical laboratory tests were collected from the electronic medical records. A clinical prediction model to estimate the risk of dying during the hospitalization were developed. Mean age (interquartile range) was 58 (45–72) years; 5421 (41%) were women, 5258 were Latinx (40%), 3805 Black (29%), 1168 White (9%), and 2959 Other (22%). During hospitalization, 2,875 were (22%) died. Using separate test and validation samples, machine learning (Gradient Boosted Decision Trees) identified eight variables—oxygen saturation, respiratory rate, systolic and diastolic blood pressures, pulse rate, blood urea nitrogen level, age and creatinine—that predicted mortality, with an area under the ROC curve (AUC) of 94%. A score based on these variables classified 5,677 (46%) as low risk (a score of 0) who had 0.8% (95% confidence interval, 0.5–1.0%) risk of dying, and 674 (5.4%) as high-risk (score ≥ 12 points) who had a 97.6% (96.5–98.8%) risk of dying; the remainder had intermediate risks. A risk calculator is available online at https://danielevanslab.shinyapps.io/Covid_mortality/. In a diverse population of hospitalized patients with COVID-19 illness, a clinical prediction model using a few readily available vital signs reflecting the severity of disease may precisely predict in-hospital mortality in diverse populations and can rapidly assist decisions to prioritize admissions and intensive care.
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影响因子：
3.7
作者：
El-Solh AA;Lawson Y;Carter M;El-Solh DA;Mergenhagen KA
通讯作者：
Mergenhagen KA
DOI：
10.1016/s1473-3099(21)00475-8
发表时间：
2022-01
期刊：
The Lancet. Infectious diseases
影响因子：
--
作者：
Twohig KA;Nyberg T;Zaidi A;Thelwall S;Sinnathamby MA;Aliabadi S;Seaman SR;Harris RJ;Hope R;Lopez-Bernal J;Gallagher E;Charlett A;De Angelis D;Presanis AM;Dabrera G;COVID-19 Genomics UK (COG-UK) consortium
通讯作者：
COVID-19 Genomics UK (COG-UK) consortium
影响因子：
13.8
作者：
Castro VM;McCoy TH;Perlis RH
通讯作者：
Perlis RH
影响因子：
2.9
作者：
Fumagalli C;Rozzini R;Vannini M;Coccia F;Cesaroni G;Mazzeo F;Cola M;Bartoloni A;Fontanari P;Lavorini F;Marcucci R;Morettini A;Nozzoli C;Peris A;Pieralli F;Pini R;Poggesi L;Ungar A;Fumagalli S;Marchionni N
通讯作者：
Marchionni N
DOI：
10.3390/ijerph17228386
发表时间：
2020-11-12
影响因子：
--
作者：
Sánchez-Montañés M;Rodríguez-Belenguer P;Serrano-López AJ;Soria-Olivas E;Alakhdar-Mohmara Y
通讯作者：
Alakhdar-Mohmara Y